About

Garvit Bansal is a highly skilled and experienced Software Engineer with a demonstrated history of working in the computer software industry. With a keen interest in building scalable systems and using data to give meaningful insights, Garvit is a versatile professional who has worked as a Software Developer at Flipkart, a Research Assistant at the Singapore University of Technology and Design, and a Senior Software Engineer at DataRobot. Garvit's expertise lies in data science and analytics, software development, Python, algorithms, and designing. He has a proven track record of delivering successful projects, including leading a project to support new data types in DataRobot, mentoring a team to build an Automated Analysis Dashboard for feature monitoring, and designing E2E APIs for Feature Engineering Project. He has also worked on CI/CD and automation projects, including setting up Jenkins pipelines for Automated Feature Engineer projects and automating the flow of testing new changes on a pull request. In his current role as a Software Engineer at meta, Garvit is working on improving the Help Center and making it smart while also adding support for agents to resolve user queries in a faster and more efficient way. His past experience at DataRobot has given him the skills to work as both a Software and Data Engineer, where he added support for low latency prediction and batch prediction for feature engineering projects over deployed models, improved batch prediction speed using binary search and caching, and supported running different kinds of separate modules as mesh. Garvit's education history includes a Bachelor of Technology (B Tech.) in Computer Science and Engineering from the LNM Institute of Information Technology. He is proficient in various tech stacks, including Flask, Spark, test, Jenkins, search, backend, and Java. With almost 8 years of relevant experience, Garvit is a highly motivated and dedicated professional with a passion for building scalable systems and delivering meaningful insights using data.